Text summarization is a process of producing a concise version of text (summary) from one or more information sources. If the generated summary preserves meaning of the original text, it will help the users to make fast and effective decision. Howeve...
In this paper, we explore the generation of face images conditioned on a textual description, as well as the capabilities of the models in editing a machine-generated image on the basis of additional text prompts. We leverage open source state-of-the...
As a quasi-public product, fishery insurance has become an important starting point for the construction of the modern fishery industry chain, supply chain and value chain risk management mechanism. We used visual data processing methods and text min...
Life-long learning is a necessity associated with the requirements of the fourth industrial revolution. Although distance online education played a major role in the evolution of the modern education system, this share grew dramatically because of th...
The increasing amount of legal information available online is overwhelming for both citizens and legal professionals, making it difficult and time-consuming to find relevant information and keep up with the latest legal developments. Automatic text...
The task of Text-to-SQL enables anyone to retrieve information from SQL databases using natural language. While this task has made substantial progress, the two primary evaluation metrics—Execution Accuracy (EXE) and Exact Set Matching Accuracy...
Grey relational analysis (GRA) is a part of the Grey system theory (GST). It is appropriate for solving problems with complicated interrelationships between multiple factors/parameters and variables. It solves multiple-criteria decision-making proble...
The education policy of the Macao Special Administrative Region is a driving factor in the investment of educational resources and the construction of a comprehensive education system. At the same time, the Macao Special Administrative Region Governm...
At present, text-guided image manipulation is a notable subject of study in the vision and language field. Given an image and text as inputs, these methods aim to manipulate the image according to the text, while preserving text-irrelevant regions. A...
Four versions of science and history texts were tailored to diverse hypothetical reader profiles (high and low reading skills and domain knowledge), generated by four Large Language Models (i.e., Claude, Llama, ChatGPT, and Gemini). The Natural Langu...
Text line segmentation is an essential stage in off-line optical character recognition (OCR) systems. It is a key because inaccurately segmented text lines will lead to OCR failure. Text line segmentation of handwritten documents is a complex and div...
Large language models (LLMs) show limited capability in processing low-resource historical languages due to insufficient training data and domain-specific linguistic structures. Korean Literary Sinitic (KLS), the principal written medium of the Joseo...
This study conducts a comprehensive evaluation of large language models (LLMs), including ChatGPT 4, ERNIE Bot 4, and Gemini Advanced, in the context of translating Buddhist texts from classical Chinese to modern English. Focusing on three distinct B...
The strictest water resources management (SWRM) policy is a critical policy to address China’s severe water shortage and pollution problems, and aims to promote sustainable water development and water governance. Based on data mining from multi...
The paper introduces a testing framework for the evaluation and validation of text line segmentation algorithms. Text line segmentation represents the key action for correct optical character recognition. Many of the tests for the evaluation of text...
Nowadays, individuals can be overwhelmed by a huge number of documents being present in daily life. Capturing the necessary details is often a challenge. Therefore, it is rather important to summarize documents to obtain the main information quickly....
A very important task of Natural Language Processing is text categorization (or text classification), which aims to automatically classify a document into categories. This kind of task includes numerous applications, such as sentiment analysis, langu...
The drum-like virtual reality (VR) keyboard is a contemporary, controller-based interface for text input in VR that uses a drum set metaphor. The controllers are used as sticks which, through downward movements, “press” the keys of the vi...
Millions of people with vision impairment or vision loss face considerable barriers in using mobile technology and services due to the difficulty of text entry. In this paper, we review related studies involving the design and evaluation of novel pro...
Book covers are often the first component seen before a reader engages with a book’s contents; therefore, careful consideration is given to the text and image features that constitute their design. This study investigates the effects of the pre...
Scene text understanding, serving as a cornerstone technology for autonomous navigation, document digitization, and accessibility tools, has witnessed a paradigm shift from traditional methods relying on handcrafted features and multi-stage processin...
19 October 2022
Nowadays, tourists increasingly prefer to check the reviews of attractions before traveling to decide whether to visit them or not. To respond to the change in the way tourists choose attractions, it is important to classify the reviews of attraction...
Parallel natural language processing systems were previously successfully tested on the tasks of part-of-speech tagging and authorship attribution through mini-language modeling, for which they achieved significantly better results than independent m...
Background: Electronic health records (EHRs) remain a vital source of clinical information, yet processing these heterogeneous data is extremely labor-intensive. Summarization of these data using Large Language Models (LLMs) is considered a promising...
The success of social robotics is directly linked to their ability of interacting with people. Humans possess verbal and non-verbal communication skills, and, therefore, both are essential for social robots to get a natural human–robot interact...
13 February 2023
Workplace health promotion programs (WHPPs) can improve shift workers’ physical activity. The purpose of this paper is to present the process evaluation of a text messaging health promotion intervention for mining shift workers during a 24-day...
This study concentrates on the investigation, development, and evaluation of Text-to-Speech Synthesis systems based on Deep Learning models for the Azerbaijani Language. We have selected and compared state-of-the-art models-Tacotron and Deep Convolut...
1 January 2020
Companies have gained important advantages by the development of electronic commerce. Consumer evaluations in electronic environment offer great possibilities for analysis. The fact that the consumer opinions are comprised of textual data, analyzes h...
In recent years, the evolution of technology has led to an increase in text data obtained from many sources. In the biomedical domain, text information has also evidenced this accelerated growth, and automatic text summarization systems play an essen...
In this article, we overview the research literature exploring the teaching of evaluative language in written and/or visual texts in the elementary years of schooling. We then review the recently redrafted Australian Curriculum: English to identify t...
9 February 2020
Background: The primary care service in Catalonia has operated an asynchronous teleconsulting service between GPs and patients since 2015 (eConsulta), which has generated some 500,000 messages. New developments in big data analysis tools, particularl...
With the advent of Transformer-based generative AI, there has been a surge in research focused on large-scale generative language models, especially in natural language processing applications. Moreover, these models have demonstrated immense potenti...
Evaluation campaigns provide a common framework with which the progress of speech technologies can be effectively measured. The aim of this paper is to present a detailed overview of the IberSpeech-RTVE 2022 Challenges, which were organized as part o...
Significant progress has been achieved in text generation due to recent developments in neural architectures; nevertheless, this task remains challenging, especially for low-resource languages. This study is centered on developing a model for abstrac...
The study sheds light on the importance of diagnostic and feedback skills regarding argumentative pupils’ texts for (prospective) teachers and the current state of research in this area. The importance of argumentation in geography education is...
Evaluation of the United States Centers for Disease Control and Prevention (CDC)-defined HCV-related risk factors are not consistently performed as part of routine care, rendering risk-based testing susceptible to clinician bias and missed diagnoses....
Patients’ discharge summaries (documents) are health sensors that are used for measuring the quality of treatment in medical centers. However, extracting information automatically from discharge summaries with unstructured natural language is c...
19 July 2021
Although many countries around the world, especially China, highlight the strategy of green development, there has been little research evaluating the effectiveness of green development policies in local area. This study explores 16 policy texts with...
The review enumerates the predominant applications of large language models (LLMs) in natural language processing (NLP) tasks, with a particular emphasis on the years 2023 to 2025. A particular emphasis is placed on applications pertaining to informa...
Industrial development cannot be separated from policy guidance and support. Scientific evaluation and analysis of wind power industrial policies can promote the sustainable and healthy development of the industry, which has great significance to acc...
The automated classification of texts into predefined categories has become increasingly prominent, driven by the exponential growth of digital documents and the demand for efficient organization. This paper serves as an in-depth survey of text class...
Synthetic medical text generation has emerged as a solution to data scarcity and privacy constraints in clinical NLP. This review systematically evaluates the use of Large Language Models (LLMs) for structured medical text generation, examining techn...
This study is intended to evaluate and contrast the performance of varying combinations of embedding algorithms and weighting systems in measuring perception-based text similarity using the Cosine Similarity approach. Within a structured experiment d...
In this paper we demonstrate a family of metrics for estimating the quality of a text summary relative to one or more human-generated summaries. The improved metrics are based on features automatically computed from the summaries to measure content a...
After nearly forty years of development, China’s land consolidation policies (CLCP) have become an important tool for promoting rural revitalization and sustainable development. However, as a major land management policy, there is still a lack...
Background/Objectives: This study aims to evaluate the response accuracy and quality of three AI chatbots—GPT-4.0, Claude-2, and Llama-2—in answering multiple-choice questions in prosthodontic and restorative dentistry. Methods: A total o...
In the context of green development, promoting the development of data elements is crucial for advancing the green and low-carbon transition and achieving China’s “dual-carbon” targets. This study quantitatively evaluates China&rsqu...
The demand for creating automatic text summarization methods has significantly emerged as a result of the web’s explosive growth in textual data and the challenge of finding re-quired information within this massive volume of data. Multi-docume...
30 July 2015
Multilingualism has become an integral part of our present lifestyle. India has twenty two registered official languages with English and Hindi being most widely used for all official activities across the nation. As both these languages are introduc...
Incident prioritization is a critical task in enterprise environments, where textual descriptions of service disruptions often contain vague or ambiguous language. Traditional machine learning models, while effective in rigid classification, struggle...
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